"Detection of Alzheimer's Disease by Machine Learning-assisted Vibrational Spectroscopy in Cerebrospinal Fluid"

Who: Laura Arevalo, Nanoengineering, CIC nanoGUNE

Place: nanoGUNE seminar room, Tolosa Hiribidea 76, Donostia - San Sebastian

Date: Monday, 23 May 2022, 11:00

Detection of Alzheimer's Disease by Machine Learning-assisted Vibrational Spectroscopy in Cerebrospinal Fluid

Dr. Laura Arevalo

Nanoengineering, CIC nanoGUNE

Nowadays, the diagnosis of Alzheimer?s disease (AD) is a complex process that involves several clinical tests such as neurological evaluation or brain scans [1]. Cerebrospinal Fluid (CSF), as it is in direct contact with the brain, is used to find biomarkers of amyloid ? pathology and tau pathology. In this talk, a new method of detection of biomarkers in CSF related with the Alzheimer?s disease is described; the methodology is based on vibrational spectroscopy analysis through machine learning prediction model [2]. Vibrational spectroscopy provides the entire biochemical composition of the CSF, in that way the detection of small changes typical of the AD can be ascertained. Infrared absorption and Raman spectra of CSF samples acquired from 22 volunteers were measured. A dataset with 610 spectra were analysed within a Machine Learning Framework. We found that a logistic regression model can discriminate between healthy and sick patients with a precision of 98% when the input for the model is the combination of the two types of spectral data. Our methodology shows high discriminative capabilities and is a proof of concept of an alternative and accurate tool for the diagnosis of AD.


[1] Dubois, B., Villain, N., Frisoni, G. B., Rabinovici, G. D., Sabbagh, M., Cappa, S., ... & Feldman, H. H. (2021). Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group. The Lancet Neurology, 20(6), 484-496.

[2] Baker, M. J., Byrne, H. J., Chalmers, J., Gardner, P., Goodacre, R., Henderson, A., ... & Sule-Suso, J. (2018). Clinical applications of infrared and Raman spectroscopy: state of play and future challenges. Analyst, 143(8), 1735-1757.

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